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Dissertation/Thesis Abstract

Operational Losses: Lessons from Seven of the Largest Rogue Trading Events in History
by Morat, Patricio Leonel, M.S., The University of North Carolina at Charlotte, 2017, 158; 10278918
Abstract (Summary)

Operational risk is the risk of losses arising from the failure of people, processes, and systems, and from external events. A general opinion is that, unlike market risk and credit risk, operational risk is idiosyncratic in the sense that when it manifests in one firm, it does not spread to other firms. This view implies the absence of contagion and that operational risk is firm-specific, not systemic, but there is some new evidence from the Federal Reserve Bank (FRB) that suggests frequencies track both firm and macro variables.

Until the emergence of the “Basel 2” reforms to banking supervision in the mid to late 90s, operational risk was largely an afterthought because these uncertainties were difficult to quantify, insure against, and manage in traditional ways. The last 15 years have witnessed the rapid emergence of operational risk from this low status to its institutionalization as a key component of enterprise risk management and global banking regulation. Some authors find it tempting to regard Nick Leeson, the “rogue” trader attributed with the destruction of the legendary Barings bank in 1995, as the true inventor of “operational risk.”

The magnitude of loss and the impact of operational risk and losses to date are difficult to ignore. We have seen an increase in the number of large operational losses during times of economic stress. The times of market and economic stress magnify the severity of the large operational losses and lead to the eventual unraveling of the losses in the public eye.

The research reveals a significant number of similarities between the cases of rogue trading. These results support the hypothesis that failures both internal and external to the companies analyzed facilitated the emergence of rogue trading activities, specially driven by fragmented control environments and incentive schemes undermining financial institutions’ risk culture.

Indexing (document details)
Advisor: McGregor, Rob R.
Commitee: Depken, II, Craig A., Iqbal, Azhar
School: The University of North Carolina at Charlotte
Department: Economics
School Location: United States -- North Carolina
Source: MAI 56/04M(E), Masters Abstracts International
Subjects: Business administration, Economics, Finance
Keywords: Machine learning, Operational losses, Operational risk, Risk culture, Risk management, Rogue trading
Publication Number: 10278918
ISBN: 978-1-369-75815-3
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